Abstract
Circular Intuitionistic Fuzzy Set (C-IFS) is the real extension of the standard Intuitionistic Fuzzy Sets (IFS), where each element is represented by a circle instead of a single value. The divergence measures for fuzzy sets are used to find the discrimination between fuzzy sets. In this study, several divergence functions for C-IFSs are defined. The investigations verify that the divergence functions respect axiomatic properties to be divergence measures. Additional qualities of divergence measures are investigated to assure good performance. Also, the C-IF entropy and dissimilarity measures are explored. Divergence-based VIKOR (“VlseKriterijumska Optimizacija I Kompromisno Resenje” and in English “multi-criteria optimization and compromise solution”) method for C-IFSs is extended and applied to the multi-criteria decision-making problems. In the end, pattern recognition and multi-period medical diagnosis problems are focused on. The numerical examples are provided to illustrate the debated methods.
•Divergence measures of the newly proposed C-IFSs are developed theoretically.•Entropy and dissimilarity measures are investigated.•VIKOR method is established and applied to health care waste disposal problems.•Pattern recognition and multi-period medical diagnosis problems are focused.